Tomographic imaging methods are characterized in that internal structures of an object to be examined can be investigated, without having to perform operative interventions thereupon. A possible type of tomographic image creation consists of a number of projections of the object to be examined from different angles. From these projections a two-dimensional cross-section or a three-dimensional volume image of the object to be examined can be calculated.
One example of such a tomographic imaging method is computed tomography. Methods for the scanning of an object to be examined with a CT system are generally known. Here, circular scanning, sequential circular scanning with advancement or spiral scans for example are used. Other types of scans too, which do not rely on circular movements are possible, thus for example scans with linear segments. With the aid of at least one X-ray source and at least one oppositely located detector, absorption data from the objects to be examined is recorded from different angles and these thus collected absorption data or projections apportioned to cross-sections through the object to be examined by means of corresponding reconstruction methods.
For the reconstruction of computed tomography images from X-ray CT data records of a computed tomography device (CT devices), that is from the established projections, so-called Filtered Back-Projection (FBP) is nowadays employed as the standard method. After the data capture a so-called “re-binning” step is generally performed, in which the data generated with the beam spreading out in a fan-like manner from the source is reordered in such a way that it exists in a form as if the detector were struck by X-ray beams approaching the detector in a parallel manner. The data is then transformed into the frequency range. A filtering takes place in the frequency range, and the filtered data is subsequently back-transformed. With the aid of the thus re-sorted and filtered data, a back-projection of the individual voxels within the volume of interest is then performed.
Iterative reconstruction methods have recently been developed. In such an iterative reconstruction method, a reconstruction of initial image data from the projection measurement data initially takes place. A convolution back-projection method can for example be used for this purpose. Synthetic projection data is then generated from this initial image data with a “projector”, a projection operator, which is intended to map the measuring system as mathematically effectively as possible. The difference from the measurement signal is then back-projected with the operator adjointed to the projector and a residual image is thus reconstructed, with which the initial image is updated. The updated image data can in turn be used to generate new synthetic projection data in a next iteration step with the aid of the projection operator, from which again to form the difference to the measuring signals, and to calculate a new residual image, with which the image data of the current iteration stage is again improved, etc. With such a method it is possible to reconstruct image data which has relatively good image sharpness but at the same time little image noise.
One disadvantage of this generally known calculation method is that in the case of a moving object to be examined, or an at least partially moving object to be examined, motion blur can occur in the image, as during the period of a scanning process for the data which is required for an image, a locational displacement of the object to be examined or of a part of the object to be examined may exist, so that the basic data resulting in an image does not reflect all spatially identical situations of the object to be examined. This problem of motion blur arises in a particularly marked manner when performing cardio CT examinations of a patient, in which because of the movement of the heart a marked motion blur can arise in the cardiac area or for examinations in which relatively rapid changes in the object to be examined are to be measured.